Method, system and apparatus for assembling a recording plan and data driven dialogs for automated communications

ABSTRACT

Method, system and apparatus for assembling a recording plan and data driven dialogs for automated communications are provided. At a computing device comprising a memory, a communication interface and a processor, the memory storing a database of statements comprising one or more of first names, last names, greeting statements, sentiment statements, influence statements, call to action statements, and legal statements: one or more statements from the database are automatically assembled, via the processor, into one or more phrases to be recorded; instructions for applying linguistic rules are associated with the one or more phrases, via the processor, including where to insert pauses in the one or more phrases; and, the recording plan, comprising the one or more phrases in association with the instructions, is stored at the memory.

CROSS-REFERENCE TO RELATED APPLICATION(S)

This application is a continuation application of U.S. patentapplication Ser. No. 14/210,912, filed Mar. 14, 2014, which isincorporated herein by reference.

FIELD

The specification relates generally to automated messaging systems, andspecifically to a method, system and apparatus for assembling arecording plan and data driven dialogs for automated communications.

BACKGROUND

Assembling recordings for automated communications, such as interactivevoice response (IVR) systems and human voice messaging systems, iscurrently quite limited, and the automated communication can soundstilted and/or unnatural, which leads to customers receiving the callshanging up.

BRIEF DESCRIPTIONS OF THE DRAWINGS

For a better understanding of the various implementations describedherein and to show more clearly how they may be carried into effect,reference will now be made, by way of example only, to the accompanyingdrawings in which:

FIG. 1 depicts a device for assembling a recording plan and data drivendialogs for automated communications, according to non-limitingimplementations.

FIG. 2 examples of statements to be used in a recording plan and/or adata driven dialog by the device of FIG. 1, according to non-limitingimplementations.

FIG. 3 examples of recorded phrases to be used in a recording planand/or a data driven dialog by the device of FIG. 1, according tonon-limiting implementations.

FIG. 4 depicts a system for assembling a recording plan and data drivendialogs for automated communications and deploying the data drivendialogs, according to non-limiting implementations.

FIG. 5 depicts an example of customer records used to generate arecording plan and/or data driven dialogs by the device of FIG. 1,according to non-limiting implementations.

FIG. 6 depicts an example of campaign data used to generate a recordingplan and/or data driven dialogs by the device of FIG. 1, according tonon-limiting implementations.

FIG. 7 depicts another example of campaign data used to generate arecording plan and/or data driven dialogs by the device of FIG. 1,according to non-limiting implementations.

FIG. 8 depicts a flowchart of a block diagram of a method for assemblinga recording plan, according to non-limiting implementations.

FIG. 9 depicts the system of FIG. 4 communicating customer records andcampaign data to the device of FIG. 1, according to non-limitingimplementations.

FIG. 10 depicts the device of FIG. 1 using the received customer recordsand the received campaign data to populate and/or update statements tobe used in a recording plan and/or a data driven dialog, according tonon-limiting implementations.

FIG. 11 depicts the statements of FIG. 2 after being updated, accordingto non-limiting implementations.

FIG. 12 depicts the device of FIG. 1 assembling a recording plan,according to non-limiting implementations.

FIG. 13 depicts an example of a recording plan, according tonon-limiting implementations.

FIG. 14 depicts another example of a recording plan, according tonon-limiting implementations.

FIG. 15 depicts the device of FIG. 1 transmitting the recording plan toa recording terminal, and receiving recorded phrases in response,according to non-limiting implementations.

FIG. 16 depicts recorded phrases stored at the device of FIG. 1 after arecording plan is implemented, according to non-limitingimplementations.

FIG. 17 depicts a flowchart of a block diagram of a method forassembling a data driven dialog, according to non-limitingimplementations.

FIG. 18 depicts the device of FIG. 1 assembling data driven dialogs,according to non-limiting implementations.

FIG. 19 depicts examples of data driven dialogs, according tonon-limiting implementations.

FIG. 20 depicts the system of FIG. 4, in which data driven dialogs aredelivered to end channels, according to non-limiting implementations.

FIG. 21 depicts the system of FIG. 4, in which an end channel connectsto a call centre and another end channel interacts with an eventtracking device, according to non-limiting implementations.

FIG. 22 depicts a flowchart of a block diagram of a method forcorrelating time-stamped data with one or more of phrases and words in arecording, according to non-limiting implementations.

FIG. 23 depicts time-stamped data being received at the device of FIG.1, within the system of FIG. 4, according to non-limitingimplementations.

FIG. 24 depicts the device of FIG. 1 producing correlation data tocorrelate time-stamped data with one or more of phrases and words in arecording, according to non-limiting implementations.

FIG. 25 depicts an example of a graph of events as a function of time ina recording, according to non-limiting implementations.

SUMMARY

In general, this disclosure is directed to a system which assembles arecording plan according to linguistic rules, causes recordings ofphrases in the recording plan to be recorded, and assembles data drivendialogs from the recordings in a one-to-one relationship with records ina customer database, the data driven dialogs comprising recordings to bedeployed in a messaging system. For example, each data driven dialog isautomatically customized for a given customer based on one or morecustomer fields in a customer database including, but not limited to,fields related to a value of the customer to an entity, such as abusiness, and a length of time that the customer has been engaged withthe entity.

In this specification, elements may be described as “configured to”perform one or more functions or “configured for” such functions. Ingeneral, an element that is configured to perform or configured forperforming a function is enabled to perform the function, or is suitablefor performing the function, or is adapted to perform the function, oris operable to perform the function, or is otherwise capable ofperforming the function.

Furthermore, as will become apparent, in this specification certainelements may be described as connected physically, electronically, orany combination thereof, according to context. In general, componentsthat are electrically connected are configured to communicate (that is,they are capable of communicating) by way of electric signals. Accordingto context, two components that are physically coupled and/or physicallyconnected may behave as a single element. In some cases, physicallyconnected elements may be integrally formed, e.g., part of asingle-piece article that may share structures and materials. In othercases, physically connected elements may comprise discrete componentsthat may be fastened together in any fashion. Physical connections mayalso include a combination of discrete components fastened together, andcomponents fashioned as a single piece.

It is understood that for the purpose of this specification, language of“at least one of X, Y, and Z” and “one or more of X, Y and Z” can beconstrued as X only, Y only, Z only, or any combination of two or moreitems X, Y, and Z (e.g., XYZ, XYY, YZ, ZZ, and the like). Similar logiccan be applied for two or more items in any occurrence of “at least one. . . ” and “one or more . . . ” language.

An aspect of the specification provides a method of assembling arecording plan for an automated communication comprising: at a computingdevice comprising a memory, a communication interface and a processor,the memory storing a database of statements comprising one or more offirst names, last names, greeting statements, sentiment statements,influence statements, call to action statements, and legal statements:automatically assembling, via the processor, one or more statements fromthe database into one or more phrases to be recorded; associating, viathe processor, instructions for applying linguistic rules with the oneor more phrases, including where to insert pauses in the one or morephrases; and, storing, at the memory, the recording plan comprising theone or more phrases in association with the instructions.

The method can further comprise: tagging one or more words in the one ormore phrases as at least one of a sentiment based word, an emotionalword, an emphasized word, and an accent to be used when recording theword; and, including in the instructions, directions to read each taggedword according to the tagging.

The database can comprise one or more tags associated with one or morewords in the statements, each of the one or more tags comprising alinguistic rule to apply to the one or more words.

The method can further comprise: determining that at least a portion ofthe one or more statements in the database correspond to one or more ofexisting recorded phrases in a recording database, the automaticallyassembling comprising automatically assembling, via the processor, onlythe one or more of the statements from the database that do notcorrespond to the one or more of the existing recorded phrases into theone or more phrases to be recorded, along with associated linguisticrules. The recording database can comprise a voice library.

The method can further comprise: transmitting, via the communicationinterface, the recording plan to a terminal associated with a recordingtalent; receiving, via the communication interface, recorded phrasescorresponding to the one or more phrases in the recording plan from theterminal; and, storing the recorded phrases in a recording database. Therecording talent can comprise one or more of a human recording talentand an automated recording talent. The method can further comprise:assembling the recorded phrases in the recording database into one ormore data driven dialogs, each of the data driven dialogs comprising arecording for the automated communication. The method can furthercomprise: processing records, comprising one or more of networkaddresses, name records and customer records; and, assembling therecorded phrases in the recording database into one or more data drivendialogs in a one-to-one relationship with the records, each of the datadriven dialogs comprising a recording for the automated communicationcustomized for each record. Customization of the one or more data drivendialogs for each of the records can comprise one or more of: including aname stored in a respective record in each of the one or more datadriven dialogs; and, selecting a respective recorded phrase from therecording database for each of the one or more data driven dialogs basedon one or more fields associated with the respective record. The one ormore fields can comprise at least one of: a network address, ageographic address, a respective geographic address associated with acustomer associated with the name, account numbers associated with thecustomer, a phone number associated with the customer, a “value”associated with the customer, a length of time that the customer hasbeen engaged with an entity associated with the records, a first date ofinteractions between the customer and the entity, a most recent date ofinteractions between the customer and the entity, and a number ofinteractions between the customer and the entity, and an expiry date ofa product purchased by the customer from the entity.

Another aspect of the specification provides a device for assembling arecording plan for an automated communication comprising: a memory, acommunication interface and a processor, the memory storing a databaseof statements comprising one or more of first names, last names,greeting statements, sentiment statements, influence statements, call toaction statements, and legal statements, the processor configured to:automatically assemble one or more statements from the database into oneor more phrases to be recorded; associate instructions for applyinglinguistic rules with the one or more phrases, including where to insertpauses in the one or more phrases; and, store, at the memory, therecording plan comprising the one or more phrases in association withthe instructions.

The processor can be further configured to: tag one or more words in theone or more phrases as at least one of a sentiment based word, anemotional word, an emphasized word, and an accent to be used whenrecording the word; and, include in the instructions, directions to readeach tagged word according to the tag.

The database can comprise one or more tags associated with one or morewords in the statements, each of the one or more tags comprising alinguistic rule to apply to the one or more words.

The processor can be further configured to: determine that at least aportion of the one or more statements in the database correspond to oneor more of existing recorded phrases in a recording database, and theprocessor can be further configured to automatically assemble the one ormore of statements from the database into one or more phrases to berecorded by automatically assembling only the one or more of thestatements from the database that do not correspond to the one or moreof the existing recorded phrases into the one or more phrases to berecorded, along with associated linguistic rules. The recording databasecan comprise a voice library.

The processor can be further configured to: transmit, via thecommunication interface, the recording plan to a terminal associatedwith a recording talent; receive, via the communication interface,recorded phrases corresponding to the one or more phrases in therecording plan from the terminal; and, store the recorded phrases in arecording database. The recording talent can comprise one or more of ahuman recording talent and an automated recording talent. The processorcan be further configured to: assemble the recorded phrases in therecording database into one or more data driven dialogs, each of thedata driven dialogs comprising a recording for the automatedcommunication. The processor can be further configured to: processrecords, comprising one or more of network addresses, name records andcustomer records; and, assemble the recorded phrases in the recordingdatabase into one or more data driven dialogs in a one-to-onerelationship with the records, each of the data driven dialogscomprising a recording for the automated communication customized foreach record. Customization of the one or more data driven dialogs foreach of the records can comprise one or more of: including a name storedin a respective record in each of the one or more data driven dialogs;and, selecting a respective recorded phrase from the recording databasefor each of the one or more data driven dialogs based on one or morefields associated with the respective record. The one or more fields cancomprise at least one of: a network address, a geographic address, arespective geographic address associated with a customer associated withthe name, account numbers associated with the customer, a phone numberassociated with the customer, a “value” associated with the customer, alength of time that the customer has been engaged with an entityassociated with the records, a first date of interactions between thecustomer and the entity, a most recent date of interactions between thecustomer and the entity, and a number of interactions between thecustomer and the entity, and an expiry date of a product purchased bythe customer from the entity.

Another aspect of the specification provides a computer program product,comprising a computer usable medium having a computer readable programcode adapted to be executed to implement a method of assembling arecording plan for an automated communication comprising: at a computingdevice comprising a memory, a communication interface and a processor,the memory storing a database of statements comprising one or more offirst names, last names, greeting statements, sentiment statements,influence statements, call to action statements, and legal statements:automatically assembling, via the processor, one or more statements fromthe database into one or more phrases to be recorded; associating, viathe processor, instructions for applying linguistic rules with the oneor more phrases, including where to insert pauses in the one or morephrases; and, storing, at the memory, the recording plan comprising theone or more phrases in association with the instructions. The computerusable medium can comprise a non-transitory computer usable medium.

Another aspect of the specification provides a method comprising: at acomputing device comprising a processor, a memory, and a communicationinterface, determining, at the processor, at least a start time ofplaying of a recording, comprising audio of one or more of phrases andwords, in an automated communication; receiving, via the communicationinterface, time-stamped data associated with events related to theplaying of the recording in the automated communication; correlating,via the processor, the time-stamped data with one or more of phrases andwords in the recording based on the start time; and, storing, in thememory, correlation data indicative of correlations between thetime-stamped data with one or more of the phrases and the words in therecording.

The recording can comprise one or more of: an audio recording, aninteractive voice call recording, a video recording, streaming data,avatar data, and browser data; and the automated communication cancomprise one or more of: an interactive voice call, a video call, and acommunication in a browser environment.

The time-stamped data can comprise one or more of: hang-ups in aninteractive voice call, receipt of data at a website associated with theautomated communication, a call to a call centre associated with theautomated communication.

The method can further comprise producing a graph of correlationsbetween the time-stamped data and the one or more phrases.

The method can further comprise producing a graph of a number oftime-stamped data events as a function of time.

Yet a further aspect of the specification provides a device comprising:a processor, a memory, and a communication interface, the processorconfigured to: determine at least a start time of playing of arecording, comprising audio of one or more of phrases and words, in anautomated communication; receive, via the communication interface,time-stamped data associated with events related to the playing of therecording in the automated communication; correlate the time-stampeddata with one or more of phrases and words in the recording based on thestart time; and, store, in the memory, correlation data indicative ofcorrelations between the time-stamped data with one or more of thephrases and the words in the recording.

The recording can comprise one or more of: an audio recording, aninteractive voice call recording, a video recording, streaming data,avatar data, and browser data; and the automated communication cancomprise one or more of an interactive voice call, a video call, and acommunication in a browser environment.

The time-stamped data can comprise one or more of: hang-ups in aninteractive voice call, receipt of data at a website associated with theautomated communication, a call to a call centre associated with theautomated communication.

The processor can be further configured to produce a graph ofcorrelations between the time-stamped data and the one or more phrases.

The processor can be further configured to produce a graph of a numberof time-stamped data events as a function of time.

Another aspect of the specification provides a computer program product,comprising a computer usable medium having a computer readable programcode adapted to be executed to implement a method comprising: at acomputing device comprising a processor, a memory, and a communicationinterface, determining, at the processor, at least a start time ofplaying of a recording, comprising audio of one or more of phrases andwords, in an automated communication; receiving, via the communicationinterface, time-stamped data associated with events related to theplaying of the recording in the automated communication; correlating,via the processor, the time-stamped data with one or more of phrases andwords in the recording based on the start time; and, storing, in thememory, correlation data indicative of correlations between thetime-stamped data with one or more of the phrases and the words in therecording. The computer usable medium can comprise a non-transitorycomputer usable medium.

DETAILED DESCRIPTION

FIG. 1 depicts a device 101 for assembling a recording plan and datadriven dialogs for automated communications, according to non-limitingimplementations. Device 101 comprises: a processor 120, a memory 122,and a communication interface 124, and optionally: a display 126, aninput device 128, a speaker 132, and a microphone 134. Communicationinterface 124 will be interchangeably referred to hereafter as interface124. Memory 122 stores a database 140 of statements 142 comprising oneor more of first names, last names, greeting statements, sentimentstatements, influence statements, call to action statements, legalstatements, and supplementary data, as described in further detailbelow. In some implementations, and as depicted, memory 122 can furtherstore linguistic rules 144 comprising one or more of rules for applyingnatural speech pronunciation to statements 142 and/or applied to phrasesin recordings, and/or used to generate instructions for applying one ormore linguistic rules to phrases to be recorded, as described in moredetail below. In particular, the linguistic rules 144 can include a ruleand/or instructions on where to insert pauses in phrases in recordingsand/or in phrases to be recorded.

As described in more detail below, memory 122 can also store a recordingdatabase 146 storing existing recorded phrases 148 (e.g. recordedphrases previously populated at recording database 146); in general,recorded phrases 148 correspond to recordings of statements 142 storedat database 140. As described in further detail below, recorded phrases148 can be used to generate data driven dialogs. Each data driven dialogcan include, but is not limited to, an audio recording, an interactivevoice call recording, a video recording, streaming data, avatar data,browser data, and the like.

Further, while database 140 and recording database 146 are depicted asseparate databases, in other implementations, databases 140, 146 can becombined in a single database.

Processor 120 is generally configured to: automatically assemble one ormore statements 142 from database 140 into one or more phrases to berecorded; associate instructions for applying linguistic rules,including but not limited to linguistic rules 144 stored at database140, with the one or more phrases, including where to insert pauses inthe one or more phrases; and, store, at the memory, a recording plancomprising the one or more phrases in association with the instructions.

Device 101 can include, but is not limited to, any suitable combinationof electronic devices, communications devices, computing devices,personal computers, servers, laptop computers, portable electronicdevices, mobile computing devices, portable computing devices, tabletcomputing devices, laptop computing devices, internet-enabled appliancesand the like. Other suitable devices are within the scope of presentimplementations.

In implementations where device 101 comprises a server, device 101 canbe based on any well-known server environment including a module thathouses one or more central processing units, volatile memory (e.g.random access memory), persistent memory (e.g. hard disk devices) andnetwork interfaces to allow device 101 to communicate over a link tocommunication network 303. For example, device 101 can be a Sun FireV480 running a UNIX operating system, from Sun Microsystems, Inc. ofPalo Alto Calif., and having four central processing units eachoperating at about nine-hundred megahertz and having about sixteengigabytes of random access memory. However, it is to be emphasized thatthis particular server is merely exemplary, and a vast array of othertypes of computing environments for device 101 are contemplated. It isfurther more appreciated that device 101 can comprise any suitablenumber of servers that can perform different functionality of serverimplementations described herein.

Further, when device 101 comprises a server, device 101 need notcomprise optional display 126, input device 128, speaker 132, and/ormicrophone 134, but rather interactions with device 101 occur viacommunications with an external device using a suitable connectionand/or link and/or interface 124 and optionally a communicationsnetwork.

Otherwise device 101 can comprise at least one input device 128generally configured to receive input data, and can comprise anysuitable combination of input devices, including but not limited to akeyboard, a keypad, a pointing device, a mouse, a track wheel, atrackball, a touchpad, a touch screen and the like. Other suitable inputdevices are within the scope of present implementations.

Input from interface 124, and/or input device 128, is received atprocessor 120 (which can be implemented as a plurality of processors,including but not limited to one or more central processors (CPUs)).Processor 120 is configured to communicate with a memory 122 comprisinga non-volatile storage unit (e.g. Erasable Electronic Programmable ReadOnly Memory (“EEPROM”), Flash Memory) and a volatile storage unit (e.g.random access memory (“RAM”)). Programming instructions that implementthe functional teachings of device 101 as described herein are typicallymaintained, persistently, in memory 122 and used by processor 120 whichmakes appropriate utilization of volatile storage during the executionof such programming instructions. Those skilled in the art will nowrecognize that memory 122 is an example of computer readable media thatcan store programming instructions executable on processor 120.Furthermore, memory 122 is also an example of a memory unit and/ormemory module.

Memory 122 further stores an application 155 that, when processed byprocessor 120, enables processor 120 to: automatically assemble one ormore statements 142 from database 140 into one or more phrases to berecorded; associate instructions for applying linguistic rules,including by not limited to linguistic rules 144 stored at database 140,with the one or more phrases, including where to insert pauses in theone or more phrases; and, store, at the memory, a recording plancomprising the one or more phrases in association with the instructions.Application 155 can further include instructions for assembling datadriven dialogs and/or for correlating time-stamped data with recordings,as described in further detail below.

Furthermore, memory 122 storing application 155 is an example of acomputer program product, comprising a non-transitory computer usablemedium having a computer readable program code adapted to be executed toimplement a method, for example a method stored in application 155.

Processor 120 can be further configured to communicate with optionaldisplay 126, microphone 134 and/or speaker 132. Display 126 comprisesany suitable one of, or combination of, flat panel displays (e.g. LCD(liquid crystal display), plasma displays, OLED (organic light emittingdiode) displays, capacitive or resistive touchscreens, CRTs (cathode raytubes) and the like). Microphone 134 comprises any suitable microphonefor receiving sound and converting to audio data. Speaker 132 comprisesany suitable speaker for converting audio data to sound to provide oneor more of audible alerts, audible communications from remotecommunication devices, and the like. In some implementations, display126, input device 128, speaker 132 and/or microphone 134 can be externalto device 101, with processor 120 in communication with each of inputdevice 128 and display 126 via a suitable connection and/or link.

Processor 120 also connects to communication interface 124(interchangeably referred to interchangeably as interface 124), whichcan be implemented as one or more radios and/or connectors and/ornetwork adaptors and/or transceivers, configured to wirelesslycommunicate with one or more communication networks (see FIG. 4). Itwill be appreciated that interface 124 is configured to correspond withnetwork architecture that is used to implement one or more communicationlinks to the one or more communication networks, including but notlimited to any suitable combination of USB (universal serial bus)cables, serial cables, wireless links, cell-phone links, cellularnetwork links (including but not limited to 2G, 2.5G, 3G, 4G+ such asUMTS (Universal Mobile Telecommunications System), GSM (Global Systemfor Mobile Communications), CDMA (Code division multiple access), FDD(frequency division duplexing), LTE (Long Term Evolution), TDD (timedivision duplexing), TDD-LTE (TDD-Long Term Evolution), TD-SCDMA (TimeDivision Synchronous Code Division Multiple Access) and the like),wireless data, Bluetooth links, NFC (near field communication) links,WLAN (wireless local area network) links, WiFi links, WiMax links,packet based links, the Internet, analog networks, the PSTN (publicswitched telephone network), access points, and the like, and/or acombination.

While not depicted, device 101 further comprises a power source, forexample a connection to a mains power supply and a power adaptor (e.g.and AC-to-DC (alternating current to direct current) adaptor, and thelike).

In any event, it should be understood that a wide variety ofconfigurations for device 101 are contemplated.

Attention is now directed to FIG. 2 which depicts non-limitingimplementations of statements 142 stored at database 140. Whilestatements 142 are presented as grouped statement categories, asdescribed hereafter, it is understood that statements 142 can be storedin any suitable format and need not be arranged as depicted; forexample, statements 142 can be stored in a database format.

Statements 142 include, but are not limited to: first names 201, lastnames 203, greeting statements 205, sentiment statements 207, influencestatements and/or call to action statements 209 (interchangeablyreferred to hereafter as influence statements 209), legal statements211, and optional supplementary data 213. As depicted, database 140stores two names under first names 201, two names under last names 203,and one statement each under each of greeting statements 205, influencestatements 209, two statements under legal statements 211, and threestatements under sentiment statements 207. Further, the second legalstatement can comprise a field <LEGAL PHONE NUMBER> into which a phonenumber can be inserted when an associated recording of the legalstatement is being generated; indeed, throughout this specification,fields where data can be inserted are depicted with a structure of<FIELD>, though other formats are within the scope of presentimplementations. However, it is appreciated that the second legalstatement is merely example and is not to be considered unduly limiting;for example, some implementations can include legal statements with alegal phone number field, while others do not.

Statements 142 can further comprise supplementary data 213 which caninclude, but is not limited to, a list of phone numbers for populatingthe <LEGAL PHONE NUMBER> field, the list of phone numbers comprisingphone numbers to call to opt out of receiving automated voice messages,indexed by jurisdiction and/or geographic location. While not depicted,database 140 can optionally further store data on which jurisdictionsask that legal statements to be added to automated messaging systemcalls.

Further population of statements 142 will be described below withrespect to FIGS. 8-11.

FIG. 2 further depicts a non-limiting example linguistic rules 144; asdepicted linguistic rules 144 comprise four rules, though in otherimplementations linguistic rules 144 can comprise fewer than four rulesor more than four rules; linguistic rules 144 can be added, deletedand/or modified by an administrator of device 101 and/or by usingheuristic learning and/or automated heuristic learning at device 101.Further, at least one linguistic rule 144 comprises a rule on where toinsert pauses in one or more phrases to be used in data driven dialogs,for example, after influence statements, after commas, after semicolonsand the like.

However, other linguistic rules 144 can comprise a list of words toemphasize in one or more phrases to be recorded for generation of datadriven dialogs, for example the words “always”, “value”, “hope”,“useful”, “expire” and “calling”. In other words, certain words can betagged as at least one of a sentiment based word, an emotional word,and/or an emphasized word. In further implementations, linguistic rules144 can include further instructions on how to record words in one ormore phrases to be recorded, for example, sentimentally, emotionally,and the like.

Other linguistic rules are within the scope of present implementations,including, but not limited to, grammatical rules, rules associated withdialects, rules associated with regional grammar, slang, and/orpronunciation, rules associated with specific languages and the like.With regards to specific languages, while present implementations aredescribed with respect to English, in other implementations statements142, and associated linguistic rules 144, can be provided in anylanguage. Further, while linguistic rules 144 are depicted asinstruction statements (for example to be included in a recording plan),in other implementations, linguistic rules 144 can be provided accordingto any suitable linguistic rule notations, and/or as software code, forexample for interpretation by an automated recording talent, asdescribed below.

Attention is next directed to FIG. 3, which depicts a non-limitingexample of recorded phrases 148 stored at recording database 146. Whilerecorded phrases 148 are depicted as stored in rows, it is understoodthat recorded phrases 148 can be stored in any suitable format and neednot be arranged as depicted; for example, recorded phrases 148 can bestored in a database format. Specifically, recorded phrases 148comprises audio recordings to be used in data driven dialogs; asdepicted, recorded phrases 148 have been pre-populated with audiorecordings of statements 142 stored at database 140, with each line inrecorded phrases 148 corresponding to a statement 142, as well as otherwords that can be used in data driven dialogs, such as “In” and “Your”.While recorded phrases 148 in FIG. 3 are depicted as text, it isappreciated that they are stored as audio files, indexed according tocorresponding text.

Furthermore, while not depicted, each version of recorded phrases 148can exist more than once in recording database 146, for example recordedaccording to regional accents, and/or recorded by more than onerecording talent (e.g. a male recording talent and/or a female recordingtalent).

Further, while not depicted, in some implementations, each recordedphrase 148 in recording database 146 can be categorized as one or moreof a first name recording, a last name recording, a greeting statementrecording, a sentiment statement recording, an influence statementrecording, a call to action statement recording, a legal statementrecording, and a supplemental data recording.

While not depicted, recorded phrases 148 can include common words,numbers, dates, months, days of weeks, years, and the like, and indexedaccordingly.

Attention is next directed to FIG. 4, which depicts a system 300comprising: device 101, and a client device 301 in communication via acommunication network 303, interchangeably referred to hereafter asnetwork 303. Client device 301 will be interchangeably referred tohereafter as device 301. System 300 further comprises a recordingterminal 305, end channels terminals 307-1, 307-2, 307-3 . . . 307-n,and optionally at least one event tracking device 309, and a call centre311. End channels 307-1, 307-2, 307-3 . . . 307-n will beinterchangeably referred to hereafter, collectively, as end channels307, and generically as an end channel 307.

In general, system 300 can be used to generate and deliver data drivendialogs to end channels 307. Each data driven dialog comprising arecording customized for a given end channel 307, each data drivendialog automatically generated using recorded phrases 148 in aone-to-one relationship with end channels 307 therewith and/or in aone-to-one relationship with customers of an entity associated withdevice 301. The data driven dialogs can then be delivered to endchannels 307 using network 303.

Device 301 can be substantially similar to device 101; for exampledevice 301 can also comprise a respective processor 320 interconnectedwith a memory 322 and a communication interface 324 (also referred tointerchangeably as interface 324), each respectively similar toprocessor 120, memory 122, and interface 124. While not depicted, device301 can further comprise an input device, a display, a speaker and/or amicrophone, similar to device 101. In some implementations device 301comprises a server similar to that described above with reference todevice 101.

While only one device 301 is depicted, any number of devices 301 iswithin the scope of present implementations, including, but not limitedto, tens, hundreds and thousands of devices 301. For example, an entityassociated with device 101 can provide a service for an entityassociated with device 301 (e.g. the entity associated with device 301can be a client of the entity associated with device 101, and the entityassociated with device 101 can have tens and/or hundreds and/orthousands of clients, and/or more clients, etc.).

Device 301 further stores, at memory 322, a customer database 332comprising customer records 333, which can comprise one more of namerecords and customer records, associated with fields, as described infurther detail below with respect to FIG. 5.

While implementations described herein colloquially refer to “clients”and “customers”, such terms are meant to be illustrative only. Forexample, devices 101, 301 and/or end points 307 can be operated by thesame entity; furthermore, each end point 307 need not be associated witha “customer”, for example a human being. Rather, in someimplementations, one or more end points 307 can comprise computingdevice and/or a terminal and/or a data terminal and/or a kiosk wheredata driven dialogs are delivered, for example in a public space; thatis, an end point 307 can be operated by an entity and not associatedwith any given person and/or customer.

Memory 322 can further store campaign data 337 comprising one more ofgreeting statements, sentiment statements, influence statements, call toaction statements, legal statements, and supplementary data, similar tothat described above with respect to FIG. 2, and described in furtherdetail below with respect to FIGS. 6 and 7; however, initially at system300, device 301 can store a larger and/or different set of statements atcampaign data 337 as compared to statements 142 at device 101.

In general, campaign data 337 comprises data associated with anautomated voice messaging campaign (referred to hereafter as a“campaign”) that the entity associated with device 301 desires toimplement by contacting customers at end channels 307, for example toadvertise a service, collect bills and/or overdue accounts, and thelike. As such the entity associated device 301 can engage the entityassociated with device 101 to implement the campaign, and/or generatedata driven dialogs for the campaign, with the entity associated withdevice 301 supplying customer records 333 and campaign data 337 toimplement the campaign.

Attention is next directed to FIG. 5 which depicts a non-limitingexample of customer records 433; in other words, customer records 333can comprise customer records 333, with one customer record per row.While customer records 433 are presented in rows and columns, it isunderstood that customer records 433 can be stored in any suitableformat and need not be arranged in rows and columns; for example,customer records 433 can be stored in a database format. Customerrecords 433 generally comprise: first names and last names of customersof the entity associated with device 301, stored in electronic form, forexample “Tara Kelly”, “Andrew Hamill”, “Ken Hackl”, etc.

Fields associated with customers referenced in customer records 433 caninclude, but are not limited to: network addresses, geographicaddresses, a respective geographic address associated with eachcustomer, account numbers associated with each customer, a phone numberassociated with each customer, a “value” associated with each customer,a length of time that the customer has been engaged with the entityassociated with device 301 and/or (as depicted) a first date ofinteractions between each customer and the entity associated with device301, a most recent and/or “last” date of interactions between eachcustomer and the entity associated with device 301, and a number ofinteractions (“# Interactions”) between each customer and the entityassociated with device 301, and the like. In some non-limitingimplementations, as depicted, each of customer records 433 can includean expiry date of a product (for example a software product) purchasedby an associated customer from the entity associated with device 301.

Rather than, and/or in addition to, a phone number, each customer recordcan include one or more of associated internet protocol address, anassociated MAC (media access control) address, and the like, to identifyequipment and/or devices and/or end channels 307 associated with a givencustomer. Network addresses and/or geographic addresses can furtherinclude network addresses and/or geographic addresses, and the like, ofcomputing devices, kiosks etc., that are not specifically associatedwith a given customer. Customer records 333, 433 can further include,but are not limited to, accent information (e.g. an accent associatedwith one or more customers), regional and/or geographical and/orlocation data, language preferences, profile data (e.g. customer profiledata), and preference data (e.g. customer preference data).

Each “interaction” between a customer and the entity associated withdevice 301 can include, but is not limited to, a visit by a customer toa physical or web-based store and/or a geographic location associatedwith the entity associated with device 301, a visit by a customer to aweb site associated with the entity associated with device 301,purchasing goods and/or services and/or products from the entityassociated with device 301, borrowing money from the entity associatedwith device 301, receipt of mail, payments etc. sent by a customer tothe entity associated with device 301, and the like.

Indeed, an “interaction” can be defined by each entity according to anydefinition of an “interaction” that the entity wishes to apply. Further,an interaction between customers of the entity associated with device301 can be tracked using loyalty cards, credit cards, security cameras,purchasing histories, browser cookies, and the like.

A new customer record 433 can be added whenever the entity associatedwith device 301 gains a new customer, and the associated fields can bepopulated as data is collected about the customer; further theassociated fields can be updated as events and/or interactionsassociated with the customer occur, for example as the customerinteracts with and/or engages the entity associated with device 301.

While only five records are depicted in customer records 433, any numberof records is within the scope of present implementations, including,but not limited to, hundreds to thousands to millions of records. Forexample, an entity associated with device 301 can have thousands tomillions of customers, with one record for each customer.

Further, each customer stored in customer records 433 can be categorizedaccording to one of a number of value-based categories, as depicted“New”, “Valued”, and “Long-time”, though in other implementations, morethan three and fewer than three value based categories can be used.Further, each value-based category can be based on a given formula,which can be defined by the entity associated with device 301. Forexample: a “New” customer can be a customer whose first documentedinteraction with the entity associated with device 301 is within a yearof a current date: a “Valued” customer can be a customer whose firstdocumented interaction with the entity associated with device 301 isoutside of a year of a current date and/or that has more than 10interactions with the entity associated with device 301; and a“Long-time” customer can be a customer whose first documentedinteraction with the entity associated with device 301 is outside of ayear of a current date, and that has fewer than 10 interactions with canbe a customer whose first documented interaction with the entityassociated with device 301 is outside of a month of a current date andthat has more than 10 interactions with the entity associated withdevice 301.

Further, while each category, as depicted, is depicted as alpha-numericusing recognized words, in other implementations, each category can benumerically based (e.g. “1”, “2”, “3” for, respectively, “New”,“Valued”, and “Long-time”), and/or alpha-numeric categories which arenot based on recognized words (e.g. “N1”, “V2”, “L3”, for, respectively,“New”, “Valued”, and “Long-time”).

Furthermore, while customer records 433, as depicted, refer to specifichuman beings, customer records 433 need not comprise records of humanbeings that are specifically customers of an entity associated withdevice 301; rather, customer records 433 store information associatedwith anyone and/or any end point 307 to which a data driven dialog is tobe delivered, as described below.

Attention is next directed to FIG. 6 which depicts a non-limitingexample of campaign data 537; in other words, campaign data 337 cancomprise campaign data 537. In the depicted example, campaign data 537is for a campaign to inform customers associated with end-channels 307of expiry dates of a software product (i.e. called “AlphaPro”). Whilecampaign data 537 is presented as grouped statement categories, asdescribed hereafter, it is understood that campaign data 537 can bestored in any suitable format and need not be arranged as depicted; forexample, campaign data 537 can be stored in a database format.

Campaign data 537 generally comprise: greeting statements 505, sentimentstatements 507, influence/call to action statements 509 (interchangeablyreferred to hereafter as influence statements 509), and supplementarydata 513.

As will become apparent, supplementary data 513 comprises data that canbe used to populate fields of greeting statements 505, sentimentstatements 507, action statements 509 and/or legal statements 211 for aparticular campaign, for example a campaign associated with campaigndata 537. While only one greeting statement 505 is depicted, in otherimplementations, more than one greeting statement 505 can be included, agiven greeting statement 505 chosen for a data driven dialog based ondata in customer records 333, 433, for example, depending on whether acustomer is categorized as “New”, “Valued” or “Long-time”.

In general, greeting statements 505 comprise statements that can be usedas a greeting at the beginning of a data driven dialog for a givencustomer as stored in customer records 333, 433. As depicted greetingstatements 505 comprise a single greeting statement that comprisesfields (indicted by “< >”), which can be populated by data stored incustomer records 333, 433 and/or supplementary data 513; for example, afield <FIRST NAME> can be populated using first names stored in customerrecords 333, 433, and fields <ENTITY NAME>, <ENTITY LOCATION>, and<PRODUCT NAME> can be populated with supplementary data 513. Forexample, supplementary data 513 stores <ENTITY NAME> as “NationalSoftware”, <ENTITY LOCATION> as “Detroit”, and <PRODUCT NAME> as“AlphaPro”.

Sentiment statements 507 can comprise statements that can be used toestablish a relationship with a customer in a data driven dialog;further each sentiment statement 507 can be associated with a valuefield stored in customer records 333, 433, for example “New”, “Valued”,“Long-time”, so that a given sentiment statement 507 can be chosen for agiven data driven dialog customized for an associated customer. Asdepicted, one or more sentiment statements 507 can comprise a field,such as <PRODUCT NAME> which can be populated using data stored atsupplementary data 513; in other implementations, sentiment statements507 can comprise fields that can be populated from customer records 333,433.

Influence statements 509 can comprise statements that can be used toinfluence a behavior of a customer during a data driven dialog and/or beused as a call to action to a customer during a data driven dialog.While only one influence statement 509 is depicted, in otherimplementations, more than one influence statement 509 can be included,a given influence statement 509 chosen for a data driven dialog based ondata in customer records 333, 433, for example, depending on whether acustomer is categorized as “New”, “Valued” or “Long-time”.

As depicted, one or more influence statements 509 can comprise a field,such as <PRODUCT NAME> which can be populated in a data driven dialogusing data stored at supplementary data 513. Further, as depicted, oneor more influence statements 509 comprise a field <EXPIRY DATE> whichcan be populated in a data driven dialog using data stored at customerrecords 333, 433, for example expiry dates from FIG. 5. As depicted, oneor more influence statements 509 can comprise a field, such as <TIMEPERIOD> which can be populated in a data driven dialog using datareceived from call centre 311; in other words, the depicted influencestatement 509 comprises instructions to extend a software license bypressing “1” on a keypad (e.g. a keypad of an end channel) to beconnected to call centre 311, the instructions including a field <TIMEPERIOD> which comprises an estimated time within which a customerlistening to a data driven dialog will be called back from call centre311 by a customer service representative (“CSR”). Hence, in theseimplementations the field <TIME PERIOD> can be received from call centre311. In some implementations, the data driven dialogs can be deliveredto end channels 307 from call centre 311 and a processor at call centre311 can populate the field <TIME PERIOD> based on current wait times fora CSR; in implementations where the data driven dialogs are delivered toend channels 307 from a device other than call centre 311 (for exampledevice 101 and/or device 301), the device can query call centre 311 vianetwork 303 and receive a current wait time from call centre 311, whichcan be used to populate field <TIME PERIOD>, as described below withreference to FIG. 20.

While not depicted, campaign data 537 can further comprise an indicationof a given recording talent to be used in the associated campaign: forexample, a given male voice, a female voice, and/or a given style ofspeaking (natural, theatrical, and the like) and/or one more regionalaccents.

Attention is next directed to FIG. 7 which depicts an alternativenon-limiting example of campaign data 637; in other words, campaign data337 can comprise campaign data 637. In the depicted example, campaigndata 637 is for a campaign to inform customers associated withend-channels 307 of events occurring at stores associated with theentity associated with device 301. As with campaign data 537, campaigndata 637 is presented as grouped statement categories, with phrases ineach statement category, however it is understood that campaign data 637can be stored in any suitable format and need not be arranged asdepicted; for example, campaign data 637 can be stored in a databaseformat. Campaign data 637 generally comprise: greeting statements 605,sentiment statements 607, influence/call to action statements 609(interchangeably referred to hereafter as influence statements 609), andsupplementary data 613.

Similar to supplementary data 513, supplementary data 613 comprises datathat can be used to populate fields of greeting statements 605,sentiment statements 607, action statements 609 and/or legal statements211 for a particular campaign; however, in contrast to supplementarydata 513, supplementary data 613 comprises lists of data that areindexed by location, for example store locations; such data can include(as depicted), but is not limited to a list of store locations, a listof store manager names indexed by store location, a list of <DAYS>and/or <DATES> of events indexed by store location, and the like. Hence,for a data driven dialog for a given customer in customer records 333,433, data can be customized according to an address of a given customer.For example, in greeting statements 605 and influence statements 609, astore manager name, a store location, and a day and/or date of an eventname can be customized in a data driven dialog according to a closeststore location to the address of a given customer.

As depicted, supplementary data 613 comprises further data (specifically<GIFT NAME>) indexed by the value categories of FIG. 5, so thatassociated <GIFT NAME> fields in sentiment statements 607 can bepopulated in a data driven dialog according the value category of acustomer.

Otherwise, campaign data 637 is similar to campaign data 537 with a<STORE NAME>, <EVENT NAME> and <GIFT NAME> customized in a data drivendialog in each of greeting statements 605, sentiment statements 607,influence statements 609 and according to data in supplementary data613.

Returning to FIG. 4, recording terminal 305, interchangeably referred tohereafter as a terminal 305, can comprise a device similar to device101. Terminal 305 can be associated with a recording talent. Therecording talent can, in some implementations comprise a human recordingtalent 341, for example a human that can record phrases in a recordingplan; in these implementations, terminal 305 can comprise a speaker andmicrophone. In other implementations, the recording talent can comprisean automated recording talent, for example a combination of software andhardware elements which can generate audio files corresponding tophrases in a recording plan.

Each recording talent can be associated with a given campaign, a givenregional accent, a given style, and the like. For example, a givenrecording talent can provide recording of words and/or phrases incertain regional accents and/or have been used before in anothercampaign by the entity associated with device 301; hence, the entityassociated with device 301 can specify, for example, in campaign data337, which recording talent to use and/or which terminal 305 to use, forconsistency between campaigns.

While only one terminal 305 is depicted, any number of terminals 305 iswithin the scope of present implementations, including, but not limitedto, tens, hundreds and thousands of terminals 305. For example, asterminal 305 is associated with a recording talent, such as humanrecording talent 341, system 300 can comprise a plurality of terminals305, each associated with a different human recording talent 341, andhence a different voice for recording phrases in a recording plan. Insome implementations, the plurality of terminals 305 can be co-located,for example at a location associated with an entity that providesrecording talent for automated communications. In other implementations,terminals 305 can be located at different locations. Furthermoreassigning of a terminal 305 and/or a recording talent to a campaign canoccur manually and/or using campaign data 337 and/or using rules; forexample, when customer records 433 comprise addresses for a givengeographic region, a terminal 305 and/or an associated recording talentcan be automatically selected based on a terminal and/or an associatedrecording talented being associated with an accent for the givengeographic region. Such rules can be stored and/or applied at device 301and/or at device 101.

In some implementations, device 101 and terminal 305 can be combinedinto one device, for example, when the recording talent comprises anautomated recording talent.

Each end channel 307 can comprise one or more of a telephone, aland-line telephone, a cell phone, a mobile phone, a portable phone, amobile communication device, a portable communication device, a webdevice, a computer, a browser based device, a kiosk, signage, in-storesignage and the like. In general, each end channel 307 comprises adevice which can receive a call and/or a message, that can include arecording and/or a data driven dialog, and the like in an automatedmessaging system, an IVR system, and the like, as described in furtherdetail below. Each recording and/or data driven dialog can include, butis not limited to, an audio recording, an interactive voice callrecording, a video recording, streaming data, avatar data, and browserdata; hence each end channel 307 can include a device which can receiveand/or interact with one or more of: an audio recording, an interactivevoice call recording, a video recording, streaming data, avatar data,and browser data.

Further, while “n” end channels 307 are depicted, any number of endchannels 307 are within the scope of present implementations, including,but not limited to, thousands and/or millions of end channels 307. Forexample, each end channel 307 can correspond to a customer of the entityassociated with device 301, and/or customers specified in customerrecords 333.

Event tracking device 309 can comprise a device configured to generatetime-stamped data associated with events related to the playing of arecording in an automated communication, which can include, but is notlimited to, an interactive voice call, a video call, a voice call, and acommunication in a browser environment, as described in further detailbelow. Hence, event tracking device 309 can comprise one or more of anend channel 307, device 301, call centre 311, a web-server, and thelike.

Call centre 311 comprises one or more devices for conducting calls overcommunication network 303, for example a plurality of telephoneterminals which can be operated by CSRs. Call centre 311 can furthercomprise one or more devices for tracking call centre data, including,but not limited to, a time until a next CSR is available, and the like,which can be used to populate fields in campaign data 337, 537, 637and/or data driven dialogs.

Each device 101, device 301, terminal 305, end channels 307, eventtracking device 309, and call centre 311 are in communication withnetwork 303 via one or more respective of links, each of which caninclude any suitable combination of wired and/or wireless links, wiredand/or wireless devices and/or wired and/or wireless networks, includingbut not limited to any suitable combination of USB (universal serialbus) cables, serial cables, wireless links, cell-phone links, cellularnetwork links (including but not limited to 2G, 2.5G, 3G, 4G+, and thelike) wireless data, Bluetooth links, NFC (near field communication)links, WiFi links, WiMax links, packet based links, the Internet, analognetworks, the PSTN (public switched telephone network), access points,and the like, and/or a combination. Each device 101, device 301,terminal 305, end channels 307, and event tracking device 309 can henceinclude one or more communication interfaces (e.g. interfaces 124, 324)for communicating over respective links.

Attention is now directed to FIG. 8 which depicts a flowchartillustrating a method 800 of assembling a recording plan for anautomated communication, according to non-limiting implementations. Inorder to assist in the explanation of method 800, it will be assumedthat method 800 is performed using device 101. Furthermore, thefollowing discussion of method 800 will lead to a further understandingof device 101 and its various components. However, it is to beunderstood that device 101 and/or method 800 can be varied, and need notwork exactly as discussed herein in conjunction with each other, andthat such variations are within the scope of present implementations. Itis appreciated that, in some implementations, method 800 is implementedin device 101 by processor 120, for example by implementing application155.

It is to be emphasized, however, that method 800 need not be performedin the exact sequence as shown, unless otherwise indicated; and likewisevarious blocks may be performed in parallel rather than in sequence;hence the elements of method 800 are referred to herein as “blocks”rather than “steps”. It is also to be understood that method 800 can beimplemented on variations of device 101 as well.

At block 801, device 101 receives customer records 333 and campaign data337 from device 301. At block 803, processor 120 populates database 140using customer records 333 and campaign data 337, for example, topopulate statements 142 with first names, last names, and statements. Atblock 805, processor 120 automatically assembles one or more statements142 from database 140 into one or more phrases to be recorded. At block807, processor 120 associates instructions for applying linguistic ruleswith the one or more phrases, including where to insert pauses in theone or more phrases. At block 809, processor 120 stores, at memory 122,the recording plan comprising the one or more phrases in associationwith the instructions.

Method 800 will now be described with reference to FIGS. 9-16; withFIGS. 10 and 12 being substantially similar to FIG. 1, FIGS. 9 and 15being substantially similar to FIG. 4, FIG. 11 being substantiallysimilar to FIG. 2, and FIG. 16 being substantially similar to FIG. 3,with like elements having like numbers. It is furthermore assumed inFIGS. 9-16 that campaign data 337 comprises campaign data 537 to launcha campaign to encourage customers associated with end channels 307 toupdate a software license. In other implementations, campaign data 337can comprise campaign data 637 to launch a campaign to encouragecustomers associated with end channels 307 to attend an event at storelocations in their geographic location.

With reference to FIG. 9, device 101 receives customer records 333 andcampaign data 337 from device 301 via network 303 (e.g. at block 801 ofmethod 800). Alternatively, device 101 receives a portion of campaigndata 337 and/or a portion of customer records 333 from device 301; forexample, only those customer records 333 associated with customers whoare to be reached in a given campaign (e.g. via a data driven dialog)can be received, and/or new customer records 333 can be received,presuming that previous customer records are already stored at device101.

Similarly updated portions of campaign data 337 can be received atdevice 101 assuming that previous campaign data is already stored atdevice 101. In other words, in implementations, where device 101,receives a portion of campaign data 337 and/or a portion of customerrecords 333 from device 301, the received portion of campaign data 337and/or the received portion of customer records 333 can comprise adelta, respectively, with previously received campaign data and/orpreviously received customer records 333.

With reference to FIG. 10, processor 120 populates (e.g. at block 803 ofmethod 800) statements 142 at database 140 with customer records 333and/or campaign data 337 and/or portions thereof; furthermore, processor120 can create and/or populate customer records 933 at database 140.Customer records 933 can be similar to customer records 333 as depictedin FIG. 2. Processor 120 can further store campaign data 337 as campaigndata 937 at memory 122.

With reference to FIG. 11, processor 120 can populate and/or updatestatements 142 with campaign data 337 that is different from existingstatements 142. For example, the following sentiment statements 207 “Youare a valued customer, and always appreciate your confidence in ourproducts” and “You are a long time customer, and we value your business”already exist in statements 142 as depicted in FIG. 2. However, thesestatements also exist in campaign data 337 (assuming campaign data 337comprises campaign data 537): hence these statements are not added tostatements 142; rather statements in campaign data 337 that aredifferent from statements 142 are added to statements 142. Hence, FIG.11 depicts statements 142 updated with statements from campaign data 337that are different from existing statements in statements 142,including, but not limited to, supplementary data 213.

With reference to FIG. 12, processor 120: automatically assembles one ormore statements 142 from database 140 into one or more phrases to berecorded, and associates instructions for applying linguistic rules withthe one or more phrases, including where to insert pauses in the one ormore phrase (e.g. block 807 of method 800); and stores, at memory 122, arecording plan 1248 comprising the one or more phrases in associationwith the instructions (e.g. block 809 of method 800). In somenon-limiting implementations, data from customer records 933 can beincluded in recording plan 1248, for example when not already includedfrom statements 142 and/or linguistic rules 144; such data can include,but is not limited to, first names, last names, accent information,regional and/or geographical and/or location data, language preferences,profile data (e.g. customer profile data), and preference data (e.g.customer preference data).

Block 807 can include processor 120 determining that at least a portionof the one or more statements 142 in database 140 correspond to one ormore of existing recorded phrases 148 in a recording database 146, andautomatically assembling only the one or more of statements 142 fromdatabase 140 that do not correspond to one or more of the existingrecorded phrases 148 into the one or more phrases to be recorded, alongwith associated linguistic rules. In other words, only those statements142 which do not correspond to existing recorded phrases 148 areassembled into recording plan 1248.

For example, attention is next directed to FIG. 13 which depicts anon-limiting example of a recording plan 1348 generated by processor 120implementing method 800. Recording plan 1248 can comprise recording plan1348. Recording plan 1348 comprises a list of textual phrases to berecorded by a recording talent at terminal 305, including, but notlimited to, human recording talent 341. As depicted, recording plan 1348comprises one textual phrase per line, along with associatedinstructions for applying linguistic rules to the phrases, for examplewhere to insert pauses, as indicated by the instruction [PAUSE]. Theinstructions can be generated automatically using linguistic rules 144.

For example, with reference to FIG. 2, linguistic rules 144 includerules for inserting pauses in phrases, such as “Insert pause afterinfluence statements”, “Insert brief pause after a comma”, and “Insertbrief pause after a semicolon”. Hence, in these implementations,processor 120 can substitute the instruction [PAUSE] in recordinginstructions for commas and semicolons; in implementations, where aphrase to be recorded comprises an influence statement followed byanother statement, the instruction [PAUSE] can be inserted therebetween.

However, in other implementations, the instructions can be edited and/orgenerated, by a user reviewing recording plan 1348 and applyinglinguistic rules to the phrases to be recorded; in theseimplementations, processor 120 can add such user generated instructionsto recording plan 1348.

In depicted implementations, processor 120 can be further configuredfor: tagging one or more words in the one or more phrases as at leastone of a sentiment based word, an emotional word, an emphasized word,and an accent to be used when recording the word; and, including in theinstructions, directions to read each tagged word according to thetagging. For example, as described above, linguistic rules 144 comprisesa list of words to be emphasized when present in the phrases to berecorded. In other words, database 140 comprises one or more tagsassociated with one or more words in statements 142, each of the one ormore tags comprising a linguistic rule to apply to the one or morewords: as depicted in FIG. 2, the phrase “Emphasize” preceding words“always”, “value”, “hope”, “useful”, “expire” and “calling” acts as atag to indicate that the words in the list are to be emphasized whenrecorded.

Accordingly, these words are tagged with an asterisk (“*”) in recordingplan 1348, or the like, as words to be emphasized as they are one ormore of sentiment based words, emotional words, emphasized words, andthe like. In some implementations, the asterisk, or the like, can serveas a direction to read each tagged word according to the tagging, and/orexplicit instructions can be included on how to read the tagged words(“[*=EMPHASIZE THESE WORDS]”).

While as depicted a single tag type is used, in other implementations,more than one tag type can be used, for example to tag a word to berecorded sentimentally, emotionally, and the like.

Recording plan 1348 further comprises instructions on an accent to beused when recording the phrases, for example “[RECORD EACH PHRASE IN AWESTERN CANADIAN ACCENT]”. These instructions can be received withand/or derived from campaign data 337 and/or derived from customerrecords 333 (e.g. based on addresses of customers) and/or added by auser editing recording plan 1348 using device 101 and/or processor 120.Such instructions effectively tag every word in phrases of recordingplan 1348 to be recorded according to the indicated accent. While allwords are tagged in recording plan 1348 to be recording in the indicatedaccent, in other implementations, only specific words can be tagged forrecording in one or more given accents.

Similarly, attention is directed to FIG. 14, which depicts analternative recording plan 1448, which is substantially similar torecording plan 1348, however each word is tagged for recording in anaccent different from the accent of recording plan 1348 using theinstruction “[RECORD EACH PHRASE IN A US MIDWESTERN ACCENT]”, which canalso be received with and/or derived from campaign data 337 and/orderived from customer records 333 (e.g. based on addresses of customers)and/or added by a user editing recording plan 1348 using device 101and/or processor 120.

Recording plan 1248 can include both recording plan 1348 and recordingplan 1448, with recorded phrases that result from implementing recordingplan 1348 to be used in data driven dialogs for customers in westernCanada, and recorded phrases that result from implementing recordingplan 1448 to be used in data driven dialogs for customers in theAmerican Midwest.

In general, the instructions recording plan 1248 that are based onlinguistic rules, result in phrases in recording plan 1248 beingrecorded in natural speech pronunciation.

Attention is next directed to FIG. 15, which is substantially similar toFIG. 4, with like elements having like numbers. In FIG. 15, recordingplan 1248 is transmitted to recording terminal 305 associated with arecording talent, for example upon generation of recording plan 1248.When recording plan 1248 comprises more than one recording plan 1348,1448, each individual recording plan 1348, 1448 can be transmitted todifferent terminals 305; for example, a first recording terminal 305 canbe associated with a first accent (e.g. a human recording talent who canspeak the first accent, such as a western Canadian accent), and a secondrecording terminal 305 can be associated with a second accent (e.g. ahuman recording talent who can speak the first accent, such as anAmerican Midwestern accent). Assigning a given recording plan 1348, 1448to a given terminal 305 can occur manually and/or automatically usingrules: for example, a network address (and the like) of each recordingterminal 305 can be associated in a database (e.g. including but notlimited to database 140) with a given accent, which can be associated inthe database with a given geographic region (e.g. database dataindicating a given accent can be associated with a given terminal 305and/or a given geographic region in the database; alternatively, a giventerminal 305 can be associated with a given geographic region in thedatabase). When one or more addresses in customer database 933 arelocated in a given geographic region, a given recording plan 1348, 1448is transmitted to an associated terminal 305 with optional instructionsto record the phrases in the recording plan in the given accent.

In any event, recording plan 1248 received at terminal 305 isimplemented by the associated recording talent, whether human orautomated, and phrases corresponding to the phrases in recording plan1248 are recorded, according to the instructions for implementinglinguistic rules in recording plan 1248. Recorded phrases 1501 of theone or more phrases in recording plan 1248 are received at device 101,via interface 124, from terminal 305 (i.e. terminal 305 transmitsrecorded phrases 1501 to device 101 after the phrases are recordedand/or as each phrase is recorded).

As depicted in FIG. 16, recorded phrases 1501 are stored in recordedphrases 148 in recording database 146. In other words, FIG. 16 issubstantially similar to FIG. 3, but updated with recorded phrases 1501.Recorded phrases 1501 can further be indexed according to eachcorresponding textual phrase in recording plan 1248; hence indexing ofrecorded phrases 148 can be correspondingly updated.

In general, recorded phrases 148 comprise components available forassembly into data driven dialogs as will be described hereafter; hence,recording database 140 comprises a voice library of recorded phrasesthat can be used to assemble the data driven dialogs.

It is further appreciated that method 800 can be repeated with campaigndata 637, by receiving campaign data 637 at device 101.

Attention is now directed to FIG. 17 which depicts a flowchartillustrating a method 1700 of assembling data driven dialogs, accordingto non-limiting implementations. In order to assist in the explanationof method 1700, it will be assumed that method 1700 is performed usingdevice 101. Furthermore, the following discussion of method 1700 willlead to a further understanding of device 101 and its variouscomponents. However, it is to be understood that device 101 and/ormethod 1700 can be varied, and need not work exactly as discussed hereinin conjunction with each other, and that such variations are within thescope of present implementations. It is appreciated that, in someimplementations, method 1700 is implemented in device 101 by processor120, for example by implementing application 155.

It is to be emphasized, however, that method 1700 need not be performedin the exact sequence as shown, unless otherwise indicated; and likewisevarious blocks may be performed in parallel rather than in sequence;hence the elements of method 1700 are referred to herein as “blocks”rather than “steps”. It is also to be understood that method 1700 can beimplemented on variations of device 101 as well.

At block 1701, processor 120 processes records, comprising one or moreof name records and customer records, for example customer records 933;and at block 1703 assembles recorded phrases 148 in recording database146 into one or more data driven dialogs in a one-to-one relationshipwith the records, each of the data driven dialogs comprising a recordingfor automated communications, an interactive voice response call, andthe like, customized for each record.

Specifically, and with reference to FIG. 18, method 1700 results inprocessor 120 assembling recorded phrases 148, in recording database146, customer records 933 and alternatively campaign data 937, into oneor more data driven dialogs 1801, each of data driven dialogs 1801comprising a customized recording for an automated communication, aninteractive voice response call and/or an automated message and/or arecording to be played in an automated communication.

For example, each data driven dialog 1801 can be customized by one ormore of: including a name stored in a respective record (e.g. ofcustomer records 933) in each of the one or more data driven dialogs1801; selecting a respective recorded phrase 148 from recording database146 for each of the one or more data driven dialogs 1801 based on one ormore fields associated with the respective record; each of the one ormore fields can comprise at least one of (as described above): ageographic address associated with each customer, account numbersassociated with each customer, a phone number associated with eachcustomer, a “value” associated with each customer, a length of time thatthe customer has been engaged with the entity associated with device 301and/or a first date of interactions between each customer and the entityassociated with device 301, a most recent and/or “last” date ofinteractions between each customer and the entity associated with device301, and a number of interactions between each customer and the entityassociated with device 301, an expiry date of a product purchased by anassociated customer from the entity associated with device 301, and thelike.

Each data driven dialog 1801 can be assembled according to a formatand/or template as follows: [Greeting Statement] [Sentiment Statement][Influence Statement][Legal Statement], each portion of a data drivendialog 1801 assembled from recorded phrases 148 according to customerrecords 933 and statements stored in campaign data 937. As recordedphrases 148 have been recorded according to linguistic rules and are innatural speech pronunciation, the resulting data driven dialogs are alsoin natural speech pronunciation.

For example, attention is next directed to FIG. 19 which depicts anon-limiting example of data driven dialogs 1901 generated using method1700 from customer records 933 and campaign data 937, presuming customerrecords 933 are similar to customer records 433 and presuming campaigndata 937 is similar to campaign data 537. For example, data drivendialogs 1801 at device 101 can comprise data driven dialogs 1901 of FIG.19. Each data driven dialog 1901 is indexed using an associated phonenumber as each data driven dialog 1901 will be delivered to theassociated phone number; alternatively, each data driven dialog can beindexed using an associated internet protocol address, MAC (media accesscontrol) address and the like.

Hence, for example, for customer “Tara Kelly”, having a phone number“4035551212”, who is geographically located in Calgary, Alberta, Canada,and who is categorized as a “Valued” customer, a data driven dialog isassembled comprising: a greeting statement “Hi Tara, I'm calling fromNational Software in Detroit regarding your AlphaPro Software”, asentiment statement “You are a valued customer, and we always appreciateyour confidence in our products”, an influence statement “Your AlphaProSoftware License is set to expire on Mar. 5, 2014. To extend yourlicense please, press 1 now and a customer service representative willcall you back within <TIME PERIOD>” and a legal statement “To opt out offuture calls, call 4035554321”. The legal statement is included in thisexample the jurisdiction of Alberta is assumed to legally requiretelephone solicitations to include an “opt-out” clause; whether a legalstatement is to be included, or not, in a data driven dialog can bestored in database 140 and/or campaign data 937 and/or in any othersuitable location. The phrases “Tara”, “Mar. 5, 2014”, are populatedusing data from Tara Kelly's customer record. Furthermore, the datadriven dialog for Tara Kelly can be generated using recorded phrases 148recorded in a western Canadian accent as “Tara Kelly” has an address inwestern Canada.

In other words, the data driven dialog for Tara Kelly is assembled usingthe template, with recorded phrases chosen from recorded phrases 148according to data stored in a customer record 933 for Tara Kelly: asTara Kelly is a “Valued” customer, the associated data driven dialog istargeted specifically to her, and optionally in an accent she is used tohearing.

Similarly, for customer “Claire Smith”, having a phone number“3135551216”, who is geographically located in Detroit, Mich., USA, andwho is categorized as a “Long-time” customer, a data driven dialog isassembled comprising: a greeting statement “Hi Claire, I'm calling fromNational Software in Detroit regarding your AlphaPro Software”, asentiment statement “You are a long-time customer, and we value yourbusiness”, an influence statement “Your AlphaPro Software License is setto expire on May 5, 2014. To extend your license please, press 1 now anda customer service representative will call you back within <TIMEPERIOD>”. There is no legal statement as, in this example, thejurisdiction of Michigan is assumed to not require such statements. Thephrases “Claire”, “May 5, 2014”, are populated using data from ClaireSmith's customer record. Furthermore, the data driven dialog for ClaireSmith can be generated using recorded phrases 148 recorded in anAmerican Midwest accent as “Claire Smith” has an address in theMidwestern United States.

In other words, the data driven dialog for Claire Smith is assembledusing the template, with recorded phrases chosen from recorded phrases148 according to data stored in a customer record 933 for Claire Smith:as Claire Smith is a “Long-time” customer, the associated data drivendialog is targeted specifically to her, and optionally in an accent sheis used to hearing.

Similar data driven dialogs 1901 are generated for each customer record933 and customized accordingly. In other words, each data driven dialog1901 is generated in a one-to-one relationship with customer records933. Hence, when customer records 333, 933 comprises thousands and/ormillions of records, unique, customized data driven dialogs can beautomatically generated for each record without intervention of a humanuser: as each recorded phrase 148 has been generated using linguisticrules, including, but not limited to, linguistic rules 144, each datadriven dialog 1901 is also produced according to natural speechpronunciation.

It is further appreciated that device 101, can apply a portion oflinguistic rules 144 when generating the data driven dialogs 1901, forexample by inserting a pause after influence statements.

Furthermore, data driven dialogs for campaign data 637 can be producedin a similar manner, however, with geographic information, such a storelocation, a store manager's name, a day and/or date of an event, and thelike, customized according to a geographic location of each customer.

Attention is next directed to FIG. 20, which is substantially similar toFIG. 4, with like elements having like numbers, and depicts device 101calling end channels 307-1, 307-2 to deliver one or more data drivendialogs 1801; such an implementation assumes that a campaign to deliverdata driven dialogs 1801 is implemented at device 101, and assumes thatdevice 101 comprises apparatus for automatically initiating calls todeliver data driven dialogs 1801: hence, in these implementations,device 101 comprise an automated communication system which can include,but is not limited to, an interactive voice messaging system.

Alternatively, data driven dialogs 1801 can be transmitted to, and/oraccessed by call centre 311 and/or device 301, and calls to end channels307 can be initiated from call centre 311 and/or device 301.

As depicted, however, device 101 can request a current wait time periodfrom call centre 311, and call centre 311 can transmit current wait timeperiod data 2001 to device 101, which used current wait time period data2001 to populate the <TIME PERIOD> field in data driven dialogs 1801.Alternatively wait time period data 2001 can be requested and receivedduring calls to deliver data driven dialogs 1801.

In FIG. 20, device 101 is depicted as initiating calls 2003-1, 2003-2 toend channels 307-1, 307-2, for example using phone numbers in customerrecords 933: in particular a data driven dialog 1801 generated for agiven customer is delivered to the customer by: initiating a call2003-1, 2003-2 to an end channel 307 associated with the given customer(as identified via phone number), and playing a data driven dialog 1801over the call. A schedule for initiating calls 2003-1, 2003-2 can begenerated using any process, for example based on expiry dates stored incustomer records 933, and/or by staggering calls according to time ofday in a given geographic location, network loads and the like. Calls2003-1, 2003-2 will be interchangeably referred to hereaftercollectively as calls 2003, and generically as a call 2003.

While FIG. 20 depicts only two calls 2003, any number of calls 2003 fordelivering data driven dialogs 1801 can be made, for example a call 2003for each data driven dialog 1801 to any number of end channels 307. Whenan end channel 307 is busy and/or does not pick up a given call 2003,the given call 2003 can be repeated at a later time.

Each call 2003 can result in several actions by a customer at an endchannel 307: the user can terminate a call 2003 by hanging up; the usercan press “1” to be transferred to call centre 311 and/or to have a CSRcall the user back within a time period indicated within a data drivendialog; and/or a user can engage other media and/or channels associatedwith the entity associated with device 301, such as a website associatedwith the entity.

As depicted in FIG. 21, which is substantially similar to FIG. 4, withlike elements having like numbers, call 2003-1 was terminated before “1”was pressed, and call 2003-2 resulted in another call 2103 between endchannel 307-2 and call centre 311.

A customer associated with end channel 307-1 can, however, have accesseda website associated with the entity associated with device 301, asidentified on call 2003-1, and that interaction 2105 with the websitecan be tracked using cookies stored at the device used to access thewebsite (which can include, but is not limited to end channel 307-1, butcan also be a completely different device), and the like, by eventtracking device 309; in these implementations, event tracking device 309can comprise a server hosting a website for the entity associated withdevice 301 and/or a server for selling products and/or renewing licensesfor products associated with the entity. In other words, while call2003-1 was terminated before “1” was pressed, call 2003-1 can stillresult in an action that benefits the entity: the customer going to theentity's website to buy a product and/or renew a license, and the like.

Attention is now directed to FIG. 22 which depicts a flowchartillustrating a method 2200 of correlating time-stamped data with one ormore of phrases and words in a recording, according to non-limitingimplementations. In order to assist in the explanation of method 2200,it will be assumed that method 2200 is performed using device 101.Furthermore, the following discussion of method 2200 will lead to afurther understanding of device 101 and its various components. However,it is to be understood that device 101 and/or method 2200 can be varied,and need not work exactly as discussed herein in conjunction with eachother, and that such variations are within the scope of presentimplementations. It is appreciated that, in some implementations, method2200 is implemented in device 101 by processor 120, for example byimplementing application 155.

It is to be emphasized, however, that method 2200 need not be performedin the exact sequence as shown, unless otherwise indicated; and likewisevarious blocks may be performed in parallel rather than in sequence;hence the elements of method 2200 are referred to herein as “blocks”rather than “steps”. It is also to be understood that method 2200 can beimplemented on variations of device 101 as well.

It is further assumed in method 2200 that device 101 (and/or any devicethat originates calls 2003) comprises a clock device so that a starttime (e.g. a time of day) of a call 2003 can be determined; it isfurther assumed in method 2200 a length of each data driven dialog 1801can be determined and/or is known, for example when processor 120generates each data driven dialog 1801.

At block 2201, processor determines at least a start time of playing ofa recording, for example a data driven dialog 1801, comprising audio ofone or more of phrases and words, in an automated communication. Atblock 2203, processor 120 receives, via communication interface 124,time-stamped data associated with events related to the playing of therecording in the automated communication. At block 2205, processor 120correlates the time-stamped data with one or more of phrases and wordsin the recording based on the start time. At block 2207, processor 120stores, in memory 122, correlation data indicative of correlationsbetween the time-stamped data with one or more of the phrases and thewords in the recording. At an optional block 2209, processor 120produces: a graph of correlations between the time-stamped data and theone or more phrases and/or a graph of a number of time-stamped dataevents as a function of time.

Further, while method 2200 can be implemented using data driven dialogs1801, method 2200 can alternatively be applied to any recordings forwhich time-stamped data associated therewith can be determined and/orreceived and/or generated. For example, in method 2200, the recordingcan comprise one or more of: an automated communication recording, anaudio recording, an interactive voice call recording, a video recording,streaming data, avatar data, and browser data; and the automatedcommunication can comprise one or more of: an interactive voice call, avideo call, and a communication in a browser environment. Hence,recordings and/or data driven dialogs can alternatively be provided atbrowsers, within the context of an avatar and/or a video and/or an audioevent and/or streaming audio, and events associated therewith trackedand correlated with the recordings and/or data driven dialogs.

Further, the time-stamped data can comprise one or more of: hang-ups inan interactive voice call, receipt of data at a website associated withthe automated communications, a call to a call centre associated withthe automated communications, and the like.

For example, attention is next directed to FIG. 23 which is similar toFIG. 4, with like elements having like numbers, and where time-stampeddata 2301 is depicted as being transmitted to device 101 from eventtracking device 309, for example, in response to device 101, and thelike, playing of a recording (e.g. a data driven dialog 1801),comprising audio of one or more of phrases and words, in an automatedcommunication, including, but not limited to, placing a call 2003 asdescribed above. For example, time-stamped data 2301 can comprise a timea website was accessed in response to a call 2003 to a given end channel307, an association there between determined from cookies, and/or otheridentifying information received at event tracking device 309; in someimplementations, whenever an event occurs at event tracking device 309associated with customer records 433, 933 (assuming event trackingdevice 309 comprises a web server), event tracking device 309 cantransmit time-stamped data 2301 comprising a time of the event.

Alternatively, time-stamped data can be generated at device 101 and/or adevice where calls 2003 originated, when time-stamped data comprises atime a call 2003 was terminated (e.g. hang-ups on calls 2003 aretracked).

Attention is next directed to FIG. 24, which is substantially similar toFIG. 18, with like elements having like numbers; however FIG. 24 depictsprocessor 120 generating correlation data 2401 by correlatingtime-stamped data 2301 with one or more data driven dialogs 1801. Hence,for example, times of hang-ups on calls can be correlated with timesparticular statements were provided on calls 2003. Alternatively,web-site accesses can be correlated with times of calls 2003. Eventsrecorded in time-stamped data 2301 can be indexed according to whengiven words and/or phrases and/or statements were provided inrecordings.

For example, attention is next directed to FIG. 25 which depicts a graph2500 of graph of numbers of events associated with a recording as afunction of time, the event correlated with a start time (“0”) of arecording and/or a data driven dialog. To further illustrate this,approximate blocks of times that a greeting statement, a sentimentstatement, an influence statement and a legal statement were playedwithin a data driven dialog are indicated.

Hence graph 2500 can comprise a graph of correlations betweentime-stamped data 2401 and the one or more phrases, graph 2500 showingwhen events associated with time-stamped data 2401 occurred in relationto a time of each statement in a data driven dialog.

Alternatively, graph 2500 comprises a graph of a number of time-stampeddata events as a function of time.

For example, when the events comprise hang-ups on calls 2003, graph 2500shows when those hang-ups occurred: the bump close to “0” hence showsthat some customers hung up during a greeting statement, while a largernumber hung up at the beginning of a given sentiment statement; asmaller number hung-up during the influence statement, for example bypressing “1”, and a large number listened through to the legalstatement. In this manner, hang-ups can be correlated with givenstatement types to identify which statements holds the attention ofcustomers and which statements cause customers to hang up.

Further, graphs similar to graph 2500 can be generated for each type ofdata driven dialog, for example all data driven dialogs in a campaignthat contain the same value based greeting statement and/or the samevalue based sentiment statement and/or the same value based influencestatement. Hence, the effectiveness of each statement in data drivendialogs can be tracked.

Furthermore, the time access of graph 2500, and similar, can extendbeyond a length of associated recordings, for example to track websiteactivity, and the like, that occurs after a recording is played.

Provided herein is a system which assembles a recording plan accordingto linguistic rules, causes recordings of phrases in the recording planto be recorded, and assembles data driven dialogs from the recordings ina one-to-one relationship with records in a customer database, the datadriven dialogs comprising recordings to be deployed in a messagingsystem. For example, each data driven dialog is automatically customizedfor a given customer based on one or more customer fields in a customerdatabase including, but not limited to, fields related to a value of thecustomer to an entity, such as a business, and a length of time that thecustomer has been engaged with the entity. Furthermore, theeffectiveness of the data driven dialogs can be tracked usingtime-stamped data generated in response to delivering the data drivendialogs to end channels.

Those skilled in the art will appreciate that in some implementations,the functionality of device 101 can be implemented using pre-programmedhardware or firmware elements (e.g., application specific integratedcircuits (ASICs), electrically erasable programmable read-only memories(EEPROMs), etc.), or other related components. In other implementations,the functionality of device 101 can be achieved using a computingapparatus that has access to a code memory (not shown) which storescomputer-readable program code for operation of the computing apparatus.The computer-readable program code could be stored on a computerreadable storage medium which is fixed, tangible and readable directlyby these components, (e.g., removable diskette, CD-ROM, ROM, fixed disk,USB drive). Furthermore, it is appreciated that the computer-readableprogram can be stored as a computer program product comprising acomputer usable medium. Further, a persistent storage device cancomprise the computer readable program code. It is yet furtherappreciated that the computer-readable program code and/or computerusable medium can comprise a non-transitory computer-readable programcode and/or non-transitory computer usable medium. Alternatively, thecomputer-readable program code could be stored remotely buttransmittable to these components via a modem or other interface deviceconnected to a network (including, without limitation, the Internet)over a transmission medium. The transmission medium can be either anon-mobile medium (e.g., optical and/or digital and/or analogcommunications lines) or a mobile medium (e.g., microwave, infrared,free-space optical or other transmission schemes) or a combinationthereof.

Persons skilled in the art will appreciate that there are yet morealternative implementations and modifications possible, and that theabove examples are only illustrations of one or more implementations.The scope, therefore, is only to be limited by the claims appendedhereto.

What is claimed is:
 1. A method comprising: at a device comprising aprocessor, a communication interface, and a memory storing statementsfor use in an automated communication: automatically assembling, usingthe processor, one or more of the statements into one or more phrases tobe recorded; transmitting, from the communication interface to arecording talent terminal, a recording plan comprising the one or morephrases and instructions for applying linguistic rules to the one ormore phrases; receiving, at the communication interface from therecording talent terminal, recorded phrases corresponding to the one ormore phrases; and, assembling the recorded phrases into one or more datadriven dialogs, in a one-to-one relationship with records, each of thedata driven dialogs comprising a recording for the automatedcommunication customized for each of the records, the records comprisingone or more of network addresses, name records and customer records. 2.The method of claim 1, wherein the linguistic rules include where toinsert pauses in the one or more phrases.
 3. The method of claim 1,wherein the statements comprise one or more of first names, last names,greeting statements, sentiment statements, influence statements, call toaction statements, and legal statements.
 4. The method of claim 1,further comprising: storing, at the memory, the recording plan inassociation with the instructions; and storing the recorded phrases in arecording database.
 5. The method of claim 1, further comprising:tagging one or more words in the one or more phrases as at least one ofa sentiment based word, an emotional word, an emphasized word, and anaccent to be used when recording the word; and, including in theinstructions, directions to read each tagged word according to thetagging.
 6. The method of claim 1, wherein the statements are stored ina database comprising one or more tags associated with one or more wordsin the statements, each of the one or more tags comprising a linguisticrule to apply to the one or more words.
 7. The method of claim 6,further comprising: determining that at least a portion of the one ormore statements in the database correspond to one or more of existingrecorded phrases in a recording database, the automatically assemblingcomprising automatically assembling only the one or more of thestatements from the database that do not correspond to the one or moreof the existing recorded phrases into the one or more phrases to berecorded, along with associated linguistic rules.
 8. The method of claim1, further comprising storing the recorded phrases at a voice library.9. The method of claim 1, wherein the recording talent terminalcomprises one or more of a human recording talent terminal and anautomated recording talent terminal.
 10. The method of claim 1, whereincustomization of the one or more data driven dialogs for each of therecords comprises one or more of: including a name stored in arespective record in each of the one or more data driven dialogs; and,selecting a respective recorded phrase for each of the one or more datadriven dialogs based on one or more fields associated with therespective record.
 11. A device comprising: a processor, a communicationinterface, and a memory storing statements for use in an automatedcommunication, the processor configured to: automatically assemble oneor more of the statements into one or more phrases to be recorded;transmit, from the communication interface to a recording talentterminal, a recording plan comprising the one or more phrases andinstructions for applying linguistic rules to the one or more phrases;receive, at the communication interface from the recording talentterminal, recorded phrases corresponding to the one or more phrases;and, assemble the recorded phrases into one or more data driven dialogs,in a one-to-one relationship with records, each of the data drivendialogs comprising a recording for the automated communicationcustomized for each of the records, the records comprising one or moreof network addresses, name records and customer records.
 12. The deviceof claim 11, wherein the linguistic rules include where to insert pausesin the one or more phrases.
 13. The device of claim 11, wherein thestatements comprise one or more of first names, last names, greetingstatements, sentiment statements, influence statements, call to actionstatements, and legal statements.
 14. The device of claim 11, whereinthe processor is further configured to: store, at the memory, therecording plan in association with the instructions; and store therecorded phrases in a recording database.
 15. The device of claim 11,wherein the processor is further configured to: tag one or more words inthe one or more phrases as at least one of a sentiment based word, anemotional word, an emphasized word, and an accent to be used whenrecording the word; and, include in the instructions, directions to readeach tagged word according to the tagging.
 16. The device of claim 11,wherein the statements are stored in a database comprising one or moretags associated with one or more words in the statements, each of theone or more tags comprising a linguistic rule to apply to the one ormore words.
 17. The device of claim 16, wherein the processor is furtherconfigured to: determine that at least a portion of the one or morestatements in the database correspond to one or more of existingrecorded phrases in a recording database; and, automatically assemblethe one or more of the statements into one or more phrases byautomatically assembling only the one or more of the statements from thedatabase that do not correspond to the one or more of the existingrecorded phrases into the one or more phrases to be recorded, along withassociated linguistic rules.
 18. The device of claim 11, wherein theprocessor is further configured to store the recorded phrases at a voicelibrary.
 19. The device of claim 11, wherein the processor is furtherconfigured to customize the one or more data driven dialogs for each ofthe records by one or more of: including a name stored in a respectiverecord in each of the one or more data driven dialogs; and, selecting arespective recorded phrase for each of the one or more data drivendialogs based on one or more fields associated with the respectiverecord.
 20. A non-transitory computer-readable medium storing a computerprogram, wherein execution of the computer program is for: at a devicecomprising a processor, a communication interface, and a memory storingstatements for use in an automated communication: automaticallyassembling, using the processor, one or more of the statements into oneor more phrases to be recorded; transmitting, from the communicationinterface to a recording talent terminal, a recording plan comprisingthe one or more phrases and instructions for applying linguistic rulesto the one or more phrases; receiving, at the communication interfacefrom the recording talent terminal, recorded phrases corresponding tothe one or more phrases; and, assembling the recorded phrases into oneor more data driven dialogs, in a one-to-one relationship with records,each of the data driven dialogs comprising a recording for the automatedcommunication customized for each of the records, the records comprisingone or more of network addresses, name records and customer records.